"employees" entries

Improving Uber’s surge pricing

Should algorithmic pricing be the norm rather than the exception?

The Newport Wedge by Tom Walker on Flickr. Used under a public domain license.

Request an invitation to Next:Economy, our event aiming to shed light on the transformation in the nature of work now being driven by algorithms, big data, robotics, and the on-demand economy.

Companies want a bigger share of the pie than their competitors, capital wants a bigger share than labor (and labor wants right back), countries want a bigger share than their rivals, but true wealth comes when we make a bigger pie for everyone. Well run markets are a proven way to do that.

Surge pricing is one of Uber’s most interesting labor innovations. Faced with the problem that they don’t have enough drivers in particular neighborhoods or at particular hours, they use market mechanisms to bring more drivers to those areas. If they need more drivers, they raise the price to consumers until enough drivers are incented by the possibility of higher earnings to fill the demand. Pricing is not set arbitrarily. It is driven algorithmically by pickup time — the goal is to have enough cars on the road that a passenger will get a car within 3–5 minutes. (Lyft’s Prime Time pricing is a similar system.) Uber keeps raising the price until the pickup time falls into the desired range.

This is clearly an imperfect system. In one case, surge pricing gouged customers during a crisis, and even in more prosaic situations like bad weather, the end of a sporting event, or a holiday evening, customers can see enormous price hikes. This uncertainty undercuts the fundamental promise of the app, of cheap, on-demand transportation. If you don’t know how much the ride will cost, can you rely on it?

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A world of continous partial employment

Managers and workers benefit when both have access to data and control.

Photo illustration showing Lyft car in front of a Walmart

Request an invitation to Next:Economy, our event aiming to shed light on the transformation in the nature of work now being driven by algorithms, big data, robotics, and the on-demand economy.

Our future workplaces are increasingly managed by apps and algorithms. Is technology empowering workers, or making them ever more helpless cogs in a corporate profit machine?

When we talk about the “on-demand economy,” we are really talking about two things: the ability of a consumer to summon a vehicle, their lunch, or their groceries with the touch of an app or a few words to Siri, Cortana, or Google Now; and the lives of the workers who respond to those summons. Instant on-demand consumer services mean workers must also be available on demand.

As Logan Green of Lyft noted, his company provides “transportation as a service.” Perhaps the more general point is that it provides labor as a service. At least for now, the car comes with a driver.

Companies such as Lyft, Uber, TaskRabbit, Postmates, Upwork (and too many other new startups to count) all depend on a large pool of workers who make no set work commitments, who are bound to no schedule, but simply turn on an app when they want to work, and compete with other workers for whatever jobs are available.

These apps have gotten a lot of attention. But focusing that attention merely on “Next Economy companies” misses many of the deeper changes in the labor economy.

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